Economics and Value of Information Systems


While some research has been done to identify the dimensions of data quality and to develop methodologies of improving particular aspects of data quality, the fundamental questions of these methodologies remain vague. This paper tries to fill this gap by empirically analyzing the factors influencing the success of data quality improvements. Hereto, we develop a model for data quality improvement success. This model is evaluated using survey data from 179 respondents. The significance of the model is computed using the maximum likelihood estimation of AMOS. The results show, that organizational implementation success is positively associated with perceived data quality, whereas no significant contribution of data quality projects to perceived data quality could be observed.